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| # import torch | |
| # from pyannote.audio import Model, Inference | |
| # speaker_model = Model.from_pretrained("pyannote/embedding", | |
| # use_auth_token="") | |
| # inference = Inference(speaker_model, window="whole") | |
| # def create_speaker_embedding(audio_dir): | |
| # with torch.no_grad(): | |
| # embedding = inference(audio_dir) | |
| # embedding = torch.tensor([[embedding]]) | |
| # speaker_embeddings = torch.nn.functional.normalize(embedding, dim=-1) | |
| # return speaker_embeddings |